1. Field
Exemplary embodiments described herein are related to presence systems, and more specifically, for utilizing the presence data to estimate affect and communication preference of a user.
2. Related Art
Communication in the current workplace has moved far beyond face-to-face communication. Workers frequently consult and collaborate with others on a variety of tasks via technology-mediated channels such as email, instant messaging (IM), phone and video conferencing. These communication media offer fewer cues than face-to-face as to how best collaboration should be carried out. In these settings it is often harder for users to estimate other users' emotional state, which sorts of tasks and communication they are open to at the present time, and which communication medium they would prefer to use for such communication.
Presence systems in the related art may use a display of photo tiles with colored borders to indicate the current presence state of a user (e.g. location, current status, etc.), with the ability to view more detailed information on the user (e.g., contact information, calendar data, and communication tools are currently available for each individual). Such related art systems may also provide interaction choices to extend the current awareness information of the initiator and to facilitate a structured negotiation for a time and medium for a future conversation given awareness information about each individual.
The strength of the related art presence systems is in enabling users to estimate the availability of other users, both online and offline. Presence systems that provide medium preference estimates in addition to availability estimates would provide enhanced workplace communication and collaboration by, for example, enabling users to better determine if this is a good time to contact another user and, if so, through what means. Such presence systems may also be able to estimate of users' emotional states, their preferences in terms of how complex a communication task they are willing to participate in at the moment, and their preferred medium to do so.
Prediction systems in the related art predict the affect and communication preference of the user. Related art affect prediction has taken many different approaches to selecting evidence for predicting affect of a user. Affect prediction in the related art presumes that affective information could be deduced from various indicators, including facial expressions, gestures, vocal intonation, language and physiological factors. Methods in the related art used to derive evidence for predicting affect consider physiological factors; visual identification based on facial expressions, gesture, and pose; behavioral measures; direct or indirect user input, such as user profiles; and external sources, such as information from environmental sensors or databases. Such related art measures vary on their invasiveness, ease of use and automaticity.
Wearable sensor devices in the related art collect information regarding pupil dilation, arm movement, skin temperature, and heat flux, to infer the users' affective states. However, adding wearable sensors significantly increases the cost of a presence system and face user adoption issues as well. Users are unlikely to wear such devices for the sole purpose of providing affect information to a presence system.
Other related art methods use mood as an addition to an instant message buddy list, thereby allowing users to see the their buddies' moods, to search by mood or organize their lists by mood. Such methods use a camera-based system to recognize facial expressions and some limited gestures. These related art methods do not require users to take any actions to implement it, other than having a camera monitoring them.
The related art has also considered the user behaviors as a determinant of user affect. For example, affect can be linguistically inferred in the textual domain (e.g. text-based chat, weblog, and microblog) via word choice, word count, punctuation, and timing. However, access to the verbal content of these applications has significant privacy issues, which negatively impact their adoption and use, and is applicable only in situations where textual data is available.
Related art methods also utilize keystroke dynamics to determine users' affective states. Their method is much less invasive since it does not use that specific content, and is thus more likely to be accepted by people than methods requiring wearable sensor-based methods or text analysis. Unfortunately, their prediction model only performs well when the users type a pre-specified phrase. However unlikely it is that users would adopt wearable sensors to enable the deduction of affect information, it is even more unlikely that they would pause every few minutes to type a set phrase. In addition, even an improved method would have limited applicability, since even active computer users are not typing all the time.
A more promising approach in the related art uses external sources to predict affect. Such related art approaches use activity sensing to infer the cost of interruption. Those related systems can not only recognize office activities but also make automated decisions to defer routing communication requests, such as phone calls, based on a contactees' cost of interruption.
Contextual information including availability, interruptibility, breakpoints, and activity content can help workers decide when to contact their colleagues. Related art systems that use contextual information can identify and abstract a user's activity content (topic) from the accessed documents. The shared activity information can influence users' contact desire.
Additional related art systems also detect mood and support explicit mood sharing. Social mobile applications in the related art support explicit mood input and sharing among groups of friends. The affective information can be visually represented by color, words, and visual icons.